CN110493595A - The detection method and device of camera, storage medium and electronic device - Google Patents
The detection method and device of camera, storage medium and electronic device Download PDFInfo
- Publication number
- CN110493595A CN110493595A CN201910944618.6A CN201910944618A CN110493595A CN 110493595 A CN110493595 A CN 110493595A CN 201910944618 A CN201910944618 A CN 201910944618A CN 110493595 A CN110493595 A CN 110493595A
- Authority
- CN
- China
- Prior art keywords
- test card
- image
- image quality
- coloration
- camera
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N17/00—Diagnosis, testing or measuring for television systems or their details
- H04N17/002—Diagnosis, testing or measuring for television systems or their details for television cameras
Abstract
The invention discloses a kind of detection methods of camera and device, storage medium and electronic device.Wherein, this method comprises: obtaining the first image that target camera shoots test card, wherein the test card includes reflectance chart, coloration test card and gradation test card；It identifies the reflectance chart in first image, and the coloration test card and the gradation test card is identified by the reflectance chart；The objective image quality feature of first image is determined according to the reflectance chart, the coloration test card and the gradation test card；The image quality testing result of first image is determined according to the objective image quality feature and predetermined image quality criteria, it solves the technical issues of how assessing the image quality of camera in the case where monitoring complex background scene in the prior art, realizes the detection of the camera imaging quality under complex background.
Description
Technical field
The present invention relates to computer field, detection methods and device in particular to a kind of camera, storage medium
And electronic device.
Background technique
Camera captures scene information by the photosensitive element of front end, and different camera parameters will have a direct impact on camera shooting
Head imaging effect.The algorithm of assessment camera imaging quality passes through determining to the test card before camera lens based on test card at present
Position and parsing, the image information in available test card are simultaneously converted into camera parameter information by related algorithm.
Existing test card evaluation scheme is substantially just for self-timer camera, this is because self-timer camera is to image quality
It is more demanding, and be closer with shooting object, therefore the detailed information of test card preferably captures.And under monitoring scene, by
Farther out in the position of camera and object, test card positioning difficulty is larger, and detailed information is difficult to be captured, therefore matched skill
Art scheme is less.
For above-mentioned problem, currently no effective solution has been proposed.
Summary of the invention
The embodiment of the invention provides a kind of detection methods of camera and device, storage medium and electronic device, so that
It is few to solve the technical issues of how image quality of camera being assessed in the case where monitoring complex background scene in the prior art.
One side according to an embodiment of the present invention additionally provides a kind of detection method of camera, which is characterized in that packet
It includes:
Obtain the first image for shooting to test card of target camera, wherein the test card include reflectance chart,
Coloration test card and gradation test card；
It identifies the reflectance chart in first image, and identifies the coloration test card by the reflectance chart and be somebody's turn to do
Gradation test card；
The target image of first image is determined according to the reflectance chart, the coloration test card and the gradation test card
Qualitative character；
The imaging of first image is determined according to the objective image quality feature and predetermined image quality criteria
Quality measurements.
According to another aspect of an embodiment of the present invention, the detection device of camera is additionally provided, comprising:
First obtains module, the first image shot for obtaining target camera to test card, wherein the test
Card includes reflectance chart, coloration test card and gradation test card；
Identification module, reflectance chart in first image for identification, and should by reflectance chart identification
Coloration test card and the gradation test card；
First determining module, should for being determined according to the reflectance chart, the coloration test card and the gradation test card
The objective image quality feature of first image；
Second determining module, for being determined according to the objective image quality feature and predetermined image quality criteria
The image quality testing result of first image.
Another aspect according to an embodiment of the present invention, additionally provides a kind of computer-readable storage medium, which is situated between
Computer program is stored in matter, wherein the computer program is arranged to execute the detection method of above-mentioned camera when operation.
Another aspect according to an embodiment of the present invention, additionally provides a kind of electronic device, including memory, processor and deposits
Store up the computer program that can be run on a memory and on a processor, wherein above-mentioned processor passes through computer program and executes
The detection method of above-mentioned camera.
In embodiments of the present invention, position simultaneously criterion of identification test card by reflectance chart, according to standard testing
Card identification coloration test card and gradation test card, determine image according to reflectance chart, coloration test card and gradation test card
Qualitative character, so that the image quality to camera is assessed, it can be outdoor to interior, it is excessively bright, it secretly waits under complex backgrounds excessively
The positioning of test card is rapidly completed, realizes the image quality for detecting camera under complex background, can solve in the prior art
The problem of how image quality of camera being assessed in the case where monitoring complex background scene.
Detailed description of the invention
The drawings described herein are used to provide a further understanding of the present invention, constitutes part of this application, this hair
Bright illustrative embodiments and their description are used to explain the present invention, and are not constituted improper limitations of the present invention.In the accompanying drawings:
Fig. 1 is the schematic diagram of image quality test system according to an embodiment of the present invention；
Fig. 2 is the flow chart of the detection method of camera according to an embodiment of the present invention；
Fig. 3 is the schematic diagram of test card according to an embodiment of the present invention；
Fig. 4 is the flow chart of image characteristics extraction according to an embodiment of the present invention；
Fig. 5 is the flow chart of test card positioning according to an embodiment of the present invention；
Fig. 6 is the schematic diagram of test card degree according to an embodiment of the present invention and face binding；
Fig. 7 is the block diagram of the detection device of camera according to an embodiment of the present invention；
Fig. 8 is the block diagram one of the detection device of camera according to the preferred embodiment of the invention；
Fig. 9 is the block diagram two of the detection device of camera according to the preferred embodiment of the invention；
Figure 10 is a kind of structural schematic diagram of optional electronic device according to an embodiment of the present invention.
Specific embodiment
In order to enable those skilled in the art to better understand the solution of the present invention, below in conjunction in the embodiment of the present invention
Attached drawing, technical scheme in the embodiment of the invention is clearly and completely described, it is clear that described embodiment is only
The embodiment of a part of the invention, instead of all the embodiments.Based on the embodiments of the present invention, ordinary skill people
The model that the present invention protects all should belong in member's every other embodiment obtained without making creative work
It encloses.
It should be noted that description and claims of this specification and term " first " in above-mentioned attached drawing, "
Two " etc. be to be used to distinguish similar objects, without being used to describe a particular order or precedence order.It should be understood that using in this way
Data be interchangeable under appropriate circumstances, so as to the embodiment of the present invention described herein can in addition to illustrating herein or
Sequence other than those of description is implemented.In addition, term " includes " and " having " and their any deformation, it is intended that cover
Cover it is non-exclusive include, for example, the process, method, system, product or equipment for containing a series of steps or units are not necessarily limited to
Step or unit those of is clearly listed, but may include be not clearly listed or for these process, methods, product
Or other step or units that equipment is intrinsic.
Fig. 1 is the schematic diagram of image quality test system according to an embodiment of the present invention, such as Fig. 1, image quality test system
System 10, for the image quality of test image acquisition device 20, including image display device 1, display control unit 2, test card
Selection device 3, image quality analysis device 4；
Image display device 1 can show required test card for showing digital test card with monomer or array；
Display control unit 2, for controlling 1 display state of image display device, such as it is aobvious to be stuck in image for control digital test
Display in showing device 1 adjusts the brightness of image display device 1, saturation degree, contrast, specific grey-scale etc., does not do herein poor
It lifts, is illumination facilities when substituting traditionally on paper test card, be to provide setting when the shooting of image collecting device 20
Shooting environmental, equipment that no replacement is required can measure the various image quality parameters of image capture device 20；
Test card selection device 3 switches the display picture of image display device 1 for controlling and replacing digital test card
Face, certainly, it includes storage medium, the test card of different parameters is stored in this, when needing to switch a certain test card, test card
Selection device 3 can search it and be that image display device 4 or display control unit 2 provide the test card in storage medium
Address, for its reading；
Image quality analysis device 4 obtains captured figure for analyzing image captured by image collecting device 20
The parameter of picture, to obtain the shooting quality of image collecting device 20；
After image collecting device 20 is to the display picture photographing of image display device 1, captured by image send to image
Quality analysis apparatus 4 is analyzed, to judge its image quality.
In one embodiment of the present invention, image display device 1 includes tablet computer, portable computer or display screen
Deng.
In one embodiment of the present invention, the test result of higher precision in order to obtain, image quality analysis device 4 can
Image acquired in image collecting device 20 is analyzed, exact p-value result precision and test card are appropriate for that image is adopted
Acquisition means 1 can select the test card being more suitable for again, survey again if the test card for having higher precision and being more suitable for may be selected
It is fixed, to obtain the test result of higher precision.
Based on above-mentioned framework, the embodiment of the invention provides a kind of detection method of camera, Fig. 2 is real according to the present invention
The flow chart of the detection method of the camera of example is applied, as shown in Figure 2, comprising the following steps:
Step S202 obtains the first image for shooting to test card of target camera, wherein the test card includes
Reflectance chart, coloration test card and gradation test card；
In specific implementation, the first above-mentioned image can be acquired by image collecting devices such as cameras, be acquired
The quantity of the first image also and be not fixed.Under different application scenarios, the quantity of the first image collected can be different.
Test card in the embodiment of the present invention can be also possible to papery test card using digital test card, survey when for number
When examination card, the display state and shown survey of image display device are controlled by display control unit and test card selection device
The digital test card that examination card picture, i.e. image display device show various parameters under the environment such as brightness, the grayscale of setting, so that
Image collecting device can shoot all kinds of images under varying environment, to obtain its shooting quality, due to its shooting environmental and bat
Take the photograph object can by image display device adjust and show, equipment that no replacement is required is convenient and efficient, efficiently avoid using
To test card repeated replacement and the cumbersome brightness adjustment to shooting environmental, reduce test card reality when papery test card
Object.
Step S204 identifies the reflectance chart in first image, and by described in reflectance chart identification
Coloration test card and the gradation test card；
Specifically, above-mentioned steps S204 can specifically include:
The first image Plays test card is positioned, wherein include the letter that can be positioned in reflectance chart
Breath, with the position of the determination reflectance chart, and identifies the reflectance chart；For example, reflectance chart is two dimensional code, under
Face is illustrated localization criteria test card and criterion of identification test card so that reflectance chart is two dimensional code as an example.
Firstly, finding the positioning angle point at three angles of two dimensional code, smothing filtering is carried out to the first image, binaryzation is found
Profile screens the feature of two sub- profiles in profile, and it is two codes that area immediate 3 are found from the profile after screening
Positioning angle point.Judge 3 angle points be in where, be mainly used for the first image carry out perspective correction, judge 3 angle points
Then the point in the maximum angle technology two dimensional code upper left corner of the triangle in besieged city is determined according to the differential seat angle on this two side cried
The lower-left of other two intersection point and upper-right position identify the range of two dimensional code according to current feature.
After identifying reflectance chart, the position of the coloration test card can be determined according to the position of the reflectance chart
It sets and the position of the gradation test card, specifically, due to being tested in test card Plays test card and coloration test card, gray scale
The distance of card is certain, for example, the position of coloration test card 2cm right above reflectance chart, gray scale is surveyed in test card
Examination is stuck in the position of 2cm immediately below reflectance chart, and the size and test card in the image obtained according to shooting in test card are real
The size on border identifies that the coloration test card and the gray scale are surveyed from the position of the coloration test card and the gradation test card
Examination card, can determine the position of coloration test card and gradation test card according to the position of the first image Plays test card, from
And identify coloration test card and gradation test card.
Further, when identifying the position of the test card Plays test card, to the image outline of first image into
Row retrieval, specifically can be not according to how much removals of amount of image information test card rest part, with determine first figure
Target area comprising the first test card graphic as in；Judge whether the first test card graphic is rectangle by multilevel logic；
In the case where the judgment result is yes, the first test card graphic in the target area is converted, after being converted
Second test card graphic；The reflectance chart in the second test card graphic is positioned, to determine the reflectance chart
Position.
Further, region division is carried out to the first image, obtains above-mentioned target area.In specific implementation,
Complete first image is detected, longer time is generally required, it is also more demanding to the computing capability of hardware.In this hair
In bright embodiment, the first image is subjected to region division, the target area obtained after region division is detected, so as to
Shorten detection time, reduce the computing capability requirement for hardware.
In the embodiment of the present invention, according to the size of the first image and the information content in each region of the first image,
The first image is cut out, the target area is obtained.
In specific implementation, the first image is carried out the considerations of region division first is that the information content of the first image,
The target area obtained after region division include the first image most information amount namely target area in include
The primary picture feature of the first image contains mark card.
In specific implementation, the size of the first image is to carry out one of the considerations of region division.According to first
The difference of the size of image can take 2/3rds of the first image to be used as target area, can also take the first image
Half is as target area.
In specific implementation, synthesis can be carried out according to the size of the first image and the information content in each region to examine
Consider, region division is carried out to the first image and obtains target area.
In an alternative embodiment, image fuzzy detection can also be carried out to the target area.It is being embodied
In, whether image fuzzy detection obscures detecting the first image namely whether the first image can satisfy minimum requirements
Clarity requirement, if the first image cannot by image fuzzy detection, illustrate the first image exist obscure situation, then
The first image is not carried out in the case where further detecting, that is, can determine that the picture quality of the first image is unqualified.
In specific implementation, the process of image fuzzy detection compares other detections, and required time is shorter, the calculating to hardware
It is required that it is lower, therefore using image fuzzy detection as the first step of image quality detection process, with relatively simple detection method
It weeds out a part and needs detected image, and then promote the efficiency of detection.
Step S206 determines first image according to above-mentioned reflectance chart, coloration test card and gradation test card
Objective image quality feature；
In the embodiment of the present invention, above-mentioned steps S206 be can specifically include:
S2061, the face that can estimate target camera acquisition face according to the above-mentioned reflectance chart identified are big
It is small；Specifically, the size of the reflectance chart is obtained, the size of the reflectance chart and pre-stored reflectance chart is big
The small product with the ratio of standard faces size is determined as the face size of target camera acquisition face.
S2062 can determine the brightness value of the target camera according to the above-mentioned gradation test card identified；
Specifically, the brightness value of the target camera can be determined according to the gradation test card in the following manner: to this
Gray scale lattice in gradation test card are positioned, and determine the location information of each gray scale lattice；According to the position of each gray scale lattice
The weight and brightness of acquisition of information each gray scale lattice；The sum of products of the weight of each gray scale lattice and brightness is determined as this
The brightness value of target camera.
S2063 determines the clarity of the target camera according to the coloration test card, and according to the bright of the target camera
Angle value and the coloration test card determine the color saturation of the target camera, wherein the objective image quality feature includes
The clarity, the people are bold the small, color saturation and the brightness value.
Specifically, the clarity of the target camera can be determined according to the coloration test card in the following manner: to this
All gridiron patterns are positioned in coloration test card, determine each tessellated location information；According to each tessellated position
Confidence, which ceases, determines each tessellated pixel value；Own according in each tessellated calculated for pixel values coloration test card
The mean value or variance of tessellated pixel value；The pixel value mean value or variance and camera of coloration test card according to the pre-stored data
The mapping relations of clarity determine corresponding mesh of mean value or variance of all tessellated pixel values in the coloration test card
Mark the clarity of camera.
It is somebody's turn to do specifically, can be determined in the following manner according to the brightness value of the target camera and the coloration test card
The color saturation of target camera:
The chromatic value of the target camera is determined according to the coloration test card in the following manner:
Wherein, shouldThe first image is respectively transformed into color opposition space (Lab from rgb space
Color space, referred to as LAB) the corresponding chromatic value of color opposition dimension a, b under space,For standard drawing
As the corresponding chromatic value of color opposition dimension a, b under the space LAB；
The difference of the chromatic value of the target camera and the brightness value is determined as to the color saturation of the target camera,
That is color saturation=chromatic value-brightness value.
Step S208 determines first figure according to the objective image quality feature and predetermined image quality criteria
The image quality testing result of picture.
S202 to S208 through the above steps position simultaneously criterion of identification test card by reflectance chart, according to mark
Quasi- test card identification coloration test card and gradation test card, it is true according to reflectance chart, coloration test card and gradation test card
Determine Image quality measures, so that the image quality to camera is assessed, it can, excessively bright, excessively dark etc. complexity outdoor to interior
The positioning of test card is rapidly completed under background, realizes the image quality for detecting camera under complex background, can solve existing
The problem of how image quality of camera being assessed in the case where monitoring complex background scene in technology.
In the embodiment of the present invention, before including the first image of test card by the acquisition of target camera, it can pass through
Camera shooting includes that the image of test card, target object (face of target object) and facial image determines above-mentioned image
The range of Image quality measures in quality standard, specifically, obtaining the target camera under different shooting conditions to the test
Multiple second images that card, one or more facial images, target object are shot；
The Image quality measures of each second image in multiple second image are obtained by the test card respectively, wherein
The Image quality measures include that the clarity, the people are bold the small, color saturation and the brightness value；For each second figure
Picture determines clarity, face size, color saturation, the brightness etc. of the second image by above-mentioned mode, the mode determined
Identical as the Image quality measures of above-mentioned the first image of determination, details are not described herein.
Recognition of face is carried out to multiple second image respectively, obtains the first face characteristic of the target object, and should
Second face characteristic of one or more facial images；Recognition of face is carried out for each second image, specifically, to the second figure
As carrying out facial image feature extraction, the feature of extraction may include: visual signature, pixels statistics feature, facial image transformation
Coefficient characteristics, facial image kangaroo feature etc..It is extracted for certain features of face, it can be with Knowledge based engineering characterizing method
Or the characterizing method based on algebraic characteristic or statistical learning.The characteristics of image of extraction is matched and identified later, it is true respectively
First phase of the first face characteristic standard faces feature corresponding with the target of the target object in fixed multiple second image
It is special like the standard faces of the second face characteristic of degree and the one or more facial image and the one or more facial image
Second similarity of sign；First similarity calculated separately in multiple second image is average similar to second similarity
Degree；The range of Image quality measures in the image quality criteria is determined according to the average similarity in multiple second image.
Further, the image quality of maximum second image of average similarity is best, will be in multiple second image
The corresponding Image quality measures of maximum average similarity are determined as the first standard image quality feature, i.e., image quality is best
Image quality measures are set as the maximum image qualitative character in image quality criteria；On the contrary, average similarity is the smallest by second
The image quality of image be it is worst, the corresponding Image quality measures of minimum average B configuration similarity in multiple second image are determined
For the second standard image quality feature, i.e., set the worst Image quality measures of image quality in image quality criteria most
Small Image quality measures, finally, determine the image quality criteria in Image quality measures range be more than or equal to this second
Standard image quality feature, and it is less than or equal to the first standard image quality feature, the i.e. maximum image of image quality criteria
Qualitative character is the first standard image quality feature, and minimum image qualitative character is the second standard image quality feature.
The embodiment of the present invention according to practical application request, test by the camera imaging quality that can be used in large scale deployment
Receive, simultaneously because in actual use, the standard of camera imaging quality be all based on visual perception, can be with there is no standard
Recognition of face friendliness is associated with camera imaging quality.And according to the project characteristic of recognition of face, formulate a set of people
The camera imaging standard of face identification friendliness.Test card location algorithm under complex background, realizes the automatic positioning of algorithm
And corresponding camera parameter is calculated, through actually using, to including interior, outdoor, excessively bright, excessively dark etc. scenes can accurately determine
Position.The recognition of face friendliness concept of camera imaging is proposed, camera imaging parameter is mapped into recognition of face friendliness,
A kind of standard with meaning of one's words meaning is provided for camera imaging quality, it is ensured that camera can reach maximum under the parameter
It identifies friendliness, solves the problems, such as that the acceptance criteria of camera imaging is difficult.
Fig. 3 is the schematic diagram of test card according to an embodiment of the present invention, as shown in figure 3, in order to meet monitoring scene requirement,
A kind of hand-held is devised, suitable for the monitoring scene test card of recognition of face task, test card is shot by camera, is obtained
First image determines the characteristics of image of camera according to the first image.Fig. 4 is image characteristics extraction according to an embodiment of the present invention
Flow chart, as shown in Figure 4, comprising:
Step S401, the first image including test card of input camera acquisition；
Step S402 positions the first image Plays test card, obtains the position of reflectance chart；
Step S403 detects clarity, the face size of the first image；Specifically, face size is by existing to test card
Size on image can calculate to obtain.
Step S404, the position of coloration test card is determined according to the position of reflectance chart, and calculates coloration test card
Chromatic value Chroma；
Chromatic value Chroma can be calculated by the following formula:
Wherein,Square of color lump is corresponded to for color lump calculated,The flat of color lump is corresponded to for color lump calculated
Side,It is corresponding square of calculation template color lump,It is corresponding square of calculation template color lump.
Step S405, the position of gradation test card is determined according to the position of reflectance chart, and calculates gradation test card
Brightness value, and the difference of chromatic value and brightness value is determined as saturation degree；
Wherein, the testing algorithm of the brightness of camera is as follows:
Wherein, n is gray scale lattice, aiFor the weight of the i-th lattice, LiFor the brightness of the i-th lattice.Identification resolution chart passes through positioning chess
The position of disk lattice calculates each tessellated mean value and variance, and clarity is higher, and variance is bigger, and clarity is lower, and variance is got over
It is small.
Step S406 exports clarity, the face size, brightness value, chromatic value of the first image, saturation degree.
Since image background is more complicated under monitoring camera, and due to being hand-held, the embodiment of the present invention is mentioned
For the high detection algorithm of a kind of pair of scene robustness, candidate region is obtained by the retrieval to image outline, then by more
Whether the grade logic judgment candidate region is rectangle.However in actual use due to being handheld test card, can exist many inclined
Moving leads to final test card score inaccuracy, therefore joined rotation just with the operation of finely positioning, and Fig. 5 is real according to the present invention
The flow chart of the test card positioning of example is applied, as shown in Figure 5, comprising the following steps:
Step S501, input picture input the first above-mentioned image；
Binarization threshold is arranged in step S502；
Step S503 judges whether to detect test card profile, in the case where the judgment result is yes, executes step
S504, it is no to then follow the steps S502；
Step S504 judges whether profile is rectangle, in the case where the judgment result is yes, executes step S505, otherwise
Execute step S502；
Step S505 revolves positive test card, specifically, can pass through the available postrotational test card of following transition matrix
Image:
Wherein, x, y are original coordinates, and θ is rotation angle.Then by finding the gradient information near test point to calibration
Point carries out finely positioning, obtains more accurate Corner character.
Step S506 carries out quadratic search to the test card graphic after rotation just；
Step S507 carries out finely positioning to the test card in the test card graphic after the rotation just；
Step S508, the relevant parameter of read test card, and export result.
The embodiment of the present invention can also bind camera imaging quality and recognition of face friendliness, obtain by test card
To after the relevant parameter of camera imaging quality, how to formulate acceptance criteria is a particularly important link.It is general in the world
Image quality criteria never have and considered that camera imaging quality to the friendly of recognition of face, passed through face quality point and people
Face identifies similarity, and the image quality of camera is bound together with recognition of face.Specific implementation steps are as follows:
Step 1 is put into two human face photos and true man's comparison of aside standing beside test card, and Fig. 6 is according to this
The schematic diagram of test card degree and the face binding of inventive embodiments, as shown in fig. 6, the purpose is to be put into face and test card
It is detected under same environment, the friendliness of binding test card reading and recognition of face.
Step 2, respectively from test card read camera parameter information, from face figure obtain face characteristic, pass through face matter
The concept of amount point and recognition of face similarity, the picture quality of test card is bound with quality of human face image.
Step 3, according to steps 1 and 2, available under the conditions of same camera, the corresponding test card reading of different parameters
What divide with face quality, according to after binding as a result, camera parameter can be determined within the scope of, recognition of face friendliness is most
It is good, to formulate camera acceptance criteria.
The embodiment of the present invention can be used for the extensive examination of camera deployment of camera imaging quality, by gray scale, clearly
Degree and coloration test card, it is full-automatic to obtain camera brightness, coloration, clarity, face size and saturation parameters；In monitoring field
Under the more complex environment of scape background, a kind of completely new test card calibration algorithm is devised, which can catch under complex scene
It catches test card position and carries out the second-order correction of position automatically.
The embodiment of the present invention proposes the camera imaging quality standard of recognition of face friendliness, can guarantee and takes the photograph by the standard
As head image quality is most friendly to face recognition algorithms；For having run the scheme of a period of time, the one of detection algorithm is had modified
The problem of a little extreme scenes can not detect, and more scene standards are proposed, it ensure that the reusability of extensive acceptance scheme；It should
Algorithm ensure that in recognition of face, passenger flow is filed, and provides high quality for back-end algorithm, meet the video of algorithm requirement, thus from
Boosting algorithm effect on source.
The embodiment of the invention also provides a kind of detection device of camera, Fig. 7 is camera shooting according to an embodiment of the present invention
The block diagram of the detection device of head, as shown in fig. 7, comprises:
First obtains module 72, the first image shot for obtaining target camera to test card, wherein described
Test card includes reflectance chart, coloration test card and gradation test card；
Identification module 74, reflectance chart in first image for identification, and known by the reflectance chart
The not described coloration test card and the gradation test card；
First determining module 76, for being determined according to the reflectance chart, the coloration test card and the gradation test card
The objective image quality feature of first image；
Second determining module 78, for true according to the objective image quality feature and predetermined image quality criteria
The image quality testing result of fixed first image.
Fig. 8 is the block diagram one of the detection device of camera according to the preferred embodiment of the invention, as shown in Fig. 8, the identification
Module 74 includes:
First identification submodule 82, for being positioned to the first image Plays test card, to determine that the standard is surveyed
The position of card is tried, and identifies the reflectance chart；
First determine submodule 84, for the position according to the reflectance chart determine the coloration test card position and
The position of the gradation test card；
Second identification submodule 86, for identifying the coloration test card according to the position of the coloration test card, and according to
The position of the gradation test card identifies the gradation test card.
Optionally, which includes:
Retrieval unit is retrieved for the image outline to first image, to determine in first image comprising the
The target area of one test card graphic；
Judging unit, for judging whether the first test card graphic is rectangle by multilevel logic；
Converting unit is used in the case where the judgment result is yes, by the first test card graphic in the target area
It is converted, the second test card graphic after being converted；
First positioning unit, for being positioned to the reflectance chart in the second test card graphic, to determine the mark
The position of quasi- test card.
Fig. 9 is the block diagram two of the detection device of camera according to the preferred embodiment of the invention, and as shown in Fig. 9, this first
Determining module 76 includes:
Submodule 92 is estimated, for estimating the face size of target camera acquisition face according to the reflectance chart；
Second determines submodule 94, for determining the brightness value of the target camera according to the gradation test card；
Third determines submodule 96, for determining the clarity of the target camera according to the coloration test card, and according to
The brightness value of the target camera and the coloration test card determine the color saturation of the target camera, wherein the target
Image quality measures include that the clarity, the people are bold the small, color saturation and the brightness value.
Optionally, this is estimated submodule 92 and includes:
First acquisition unit, for obtaining the size of the reflectance chart；
First determination unit, for by the size of the reflectance chart and pre-stored reflectance chart size and standard
The product of the ratio of face size is determined as the face size of target camera acquisition face.
Optionally, which determines that submodule 96 includes:
Second positioning unit determines each tessellated for positioning to all gridiron patterns in the coloration test card
Location information；
Second determination unit, for determining each tessellated pixel value according to each tessellated location information；
Computing unit, for according to all tessellated pictures in each tessellated calculated for pixel values coloration test card
The mean value or variance of element value；
Third determination unit, pixel value mean value or variance and camera for coloration test card according to the pre-stored data
The mapping relations of clarity determine corresponding target of mean value or variance of all tessellated pixel values in the coloration test card
The clarity of camera.
Optionally, which includes:
Third positioning unit determines the position of each gray scale lattice for positioning to the gray scale lattice in the gradation test card
Confidence breath；
Second acquisition unit, for obtained according to the location information of each gray scale lattice the weights of each gray scale lattice with it is bright
Degree；
4th determination unit, for the sum of products of the weight of each gray scale lattice and brightness to be determined as target camera shooting
The brightness value of head.
Optionally, which determines that submodule 96 includes:
5th determination unit, for determining the coloration of the target camera according to the coloration test card in the following manner
Value:
Wherein, shouldThe first image is respectively transformed into the opposition dimension of the color under the space LAB from rgb space
The corresponding chromatic value of a, b is spent,The corresponding coloration of the color for being standard picture under the space LAB opposition dimension a, b
Value；
6th determination unit is taken the photograph for the difference of the chromatic value of the target camera and the brightness value to be determined as the target
As the color saturation of head.
Optionally, the device further include:
Second obtains module, for obtaining the target camera under different shooting conditions to the test card, one or more
Multiple second images that a facial image, target object are shot；
Third obtains module, for obtaining the figure of each second image in multiple second image by the test card respectively
Image quality measure feature, wherein the Image quality measures include that the clarity, the people are bold the small, color saturation and the brightness
Value；
Face recognition module obtains the of the target object for carrying out recognition of face to multiple second image respectively
Second face characteristic of one face characteristic and the one or more facial image；
Third determining module, for determining the first face characteristic of the target object in multiple second image respectively and being somebody's turn to do
Second face characteristic of the first similarity of the corresponding standard faces feature of target and the one or more facial image with should
Second similarity of the standard faces feature of one or more facial images；
Computing module, for calculating separately the flat of first similarity in multiple second image and second similarity
Equal similarity；
4th determining module, for determining the image quality criteria according to the average similarity in multiple second image
The range of middle Image quality measures.
Optionally, the 4th determining module includes:
4th determines submodule, is used for the corresponding Image quality measures of average similarity maximum in multiple second image
It is determined as the first standard image quality feature；
5th determines submodule, is used for the corresponding Image quality measures of minimum average B configuration similarity in multiple second image
It is determined as the second standard image quality feature；
6th determine submodule, for determine Image quality measures in the image quality criteria range be more than or equal to
The second standard image quality feature, and it is less than or equal to the second standard image quality feature.
Another aspect according to an embodiment of the present invention additionally provides a kind of for implementing the detection method of above-mentioned camera
Electronic device, as shown in Figure 10, which includes memory 1002 and processor 1004, is stored in the memory 1002
There is computer program, which is arranged to execute the step in any of the above-described embodiment of the method by computer program
Suddenly.
Optionally, in the present embodiment, above-mentioned electronic device can be located in multiple network equipments of computer network
At least one network equipment.
Optionally, in the present embodiment, above-mentioned processor can be set to execute following steps by computer program:
S11 obtains the first image that target camera shoots test card, wherein the test card includes that standard is surveyed
Examination card, coloration test card and gradation test card；
S12 identifies the reflectance chart in first image, and identifies the coloration test card by the reflectance chart
With the gradation test card；
S13 determines the target of first image according to the reflectance chart, the coloration test card and the gradation test card
Image quality measures；
S14 determines first image according to the objective image quality feature and predetermined image quality criteria
Image quality testing result.
Optionally, it will appreciated by the skilled person that structure shown in Fig. 10 is only to illustrate, electronic device can also
To be smart phone (such as Andro identifies mobile phone, iOS mobile phone), tablet computer, palm PC and mobile internet device
The terminal devices such as (Mobile Internet Devices, M mark), PAD.Figure 10 its not to the structure of above-mentioned electronic device
It causes to limit.For example, electronic device may also include the more or less component (such as network interface) than shown in Figure 10, or
Person has the configuration different from shown in Figure 10.
Wherein, memory 1002 can be used for storing software program and module, such as the camera in the embodiment of the present invention
Detection method and the corresponding program instruction/module of device, the software that processor 1004 is stored in memory 1002 by operation
Program and module realize the detection method of above-mentioned camera thereby executing various function application and data processing.It deposits
Reservoir 1002 may include high speed random access memory, can also include nonvolatile memory, such as one or more magnetic storage
Device, flash memory or other non-volatile solid state memories.In some instances, memory 1002 can further comprise opposite
In the remotely located memory of processor 1004, these remote memories can pass through network connection to terminal.Above-mentioned network
Example includes but is not limited to internet, intranet, local area network, mobile radio communication and combinations thereof.Wherein, memory 1002 has
Body can be, but not limited to for encryption key (including the first encryption key, second encryption key etc.) and decruption key (including the
One decruption key, second decruption key etc.) etc. information.It as an example, as shown in Figure 10, can be in above-mentioned memory 1002
But it is not limited to include the first acquisition module 72, identification module 74, the first determining module 76 in the detection device of above-mentioned camera
And second determining module 78.In addition, it can include but other modules for being not limited in the detection device one of above-mentioned camera
Unit repeats no more in this example.
Optionally, above-mentioned transmitting device 1006 is used to that data to be received or sent via a network.Above-mentioned network
Specific example may include cable network and wireless network.In an example, transmitting device 1006 includes a network adapter
(Network Interface Controller, NIC), can be connected by cable with other network equipments with router to
It can be communicated with internet or local area network.In an example, transmitting device 1006 be radio frequency (Radio Frequency,
RF) module is used to wirelessly be communicated with internet.
In addition, above-mentioned electronic device further include: display 1008, for showing above-mentioned media resource；With connection bus
1010, for connecting the modules component in above-mentioned electronic device.
The another aspect of embodiment according to the present invention additionally provides a kind of computer-readable storage medium, the storage
Computer program is stored in medium, wherein the computer program is arranged to execute the implementation of any of the above-described method when operation
Step in example.
Optionally, in the present embodiment, above-mentioned storage medium can be set to store by executing based on following steps
Calculation machine program:
S11 obtains the first image that target camera shoots test card, wherein the test card includes that standard is surveyed
Examination card, coloration test card and gradation test card；
S12 identifies the reflectance chart in first image, and identifies the coloration test card by the reflectance chart
With the gradation test card；
S13 determines the target of first image according to the reflectance chart, the coloration test card and the gradation test card
Image quality measures；
S14 determines first image according to the objective image quality feature and predetermined image quality criteria
Image quality testing result.
Optionally, in the present embodiment, those of ordinary skill in the art will appreciate that in the various methods of above-described embodiment
All or part of the steps be that the relevant hardware of terminal device can be instructed to complete by program, the program can store in
In one computer readable storage medium, storage medium may include: flash disk, read-only memory (Read-Only Memory,
ROM), random access device (Random Access Memory, RAM), disk or CD etc..
The serial number of the above embodiments of the invention is only for description, does not represent the advantages or disadvantages of the embodiments.
If the integrated unit in above-described embodiment is realized in the form of SFU software functional unit and as independent product
When selling or using, it can store in above-mentioned computer-readable storage medium.Based on this understanding, skill of the invention
Substantially all or part of the part that contributes to existing technology or the technical solution can be with soft in other words for art scheme
The form of part product embodies, which is stored in a storage medium, including some instructions are used so that one
Platform or multiple stage computers equipment (can be personal computer, server or network equipment etc.) execute each embodiment institute of the present invention
State all or part of the steps of method.
In the above embodiment of the invention, it all emphasizes particularly on different fields to the description of each embodiment, does not have in some embodiment
The part of detailed description, reference can be made to the related descriptions of other embodiments.
In several embodiments provided herein, it should be understood that disclosed client, it can be by others side
Formula is realized.Wherein, the apparatus embodiments described above are merely exemplary, such as the division of the unit, and only one
Kind of logical function partition, there may be another division manner in actual implementation, for example, multiple units or components can combine or
It is desirably integrated into another system, or some features can be ignored or not executed.Another point, it is shown or discussed it is mutual it
Between coupling, direct-coupling or communication connection can be through some interfaces, the INDIRECT COUPLING or communication link of unit or module
It connects, can be electrical or other forms.
The unit as illustrated by the separation member may or may not be physically separated, aobvious as unit
The component shown may or may not be physical unit, it can and it is in one place, or may be distributed over multiple
In network unit.It can select some or all of unit therein according to the actual needs to realize the mesh of this embodiment scheme
's.
It, can also be in addition, the functional units in various embodiments of the present invention may be integrated into one processing unit
It is that each unit physically exists alone, can also be integrated in one unit with two or more units.Above-mentioned integrated list
Member both can take the form of hardware realization, can also realize in the form of software functional units.
The above is only a preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art
For member, various improvements and modifications may be made without departing from the principle of the present invention, these improvements and modifications are also answered
It is considered as protection scope of the present invention.
Claims (15)
1. a kind of detection method of camera characterized by comprising
Obtain the first image that target camera shoots test card, wherein the test card includes reflectance chart, color
Spend test card and gradation test card；
It identifies the reflectance chart in the first image, and the coloration test card is identified by the reflectance chart
With the gradation test card；
The target of the first image is determined according to the reflectance chart, the coloration test card and the gradation test card
Image quality measures；
The imaging of the first image is determined according to the objective image quality feature and predetermined image quality criteria
Quality measurements.
2. the method according to claim 1, wherein identification the first image in the reflectance chart,
And identify that the coloration test card includes: with the gradation test card by the reflectance chart
The first image Plays test card is positioned, with the position of the determination reflectance chart, and described in identification
Reflectance chart；
The position of the coloration test card and the position of the gradation test card are determined according to the position of the reflectance chart；
The coloration test card is identified according to the position of the coloration test card, and is known according to the position of the gradation test card
The not described gradation test card.
3. according to the method described in claim 2, it is characterized in that, identifying the position packet of the test card Plays test card
It includes:
The image outline of the first image is retrieved, to determine in the first image comprising the first test card graphic
Target area；
Judge whether the first test card graphic is rectangle by multilevel logic；
In the case where the judgment result is yes, the first test card graphic in the target area is converted, is obtained
The second test card graphic after conversion；
Reflectance chart described in the second test card graphic is positioned, with the position of the determination reflectance chart.
4. according to the method described in claim 2, it is characterized in that, determining the target of the first image according to the test card
Image quality measures include:
The face size of the target camera acquisition face is estimated according to the reflectance chart；
The brightness value of the target camera is determined according to the gradation test card；
The clarity of the target camera is determined according to the coloration test card, and according to the brightness value of the target camera
And the coloration test card determines the color saturation of the target camera, wherein the objective image quality feature packet
Include the clarity, the face size, the color saturation and the brightness value.
5. according to the method described in claim 4, it is characterized in that, estimating the target camera according to the reflectance chart
Acquisition face face size include:
Obtain the size of the reflectance chart；
By multiplying for the size of the reflectance chart and pre-stored reflectance chart size and the ratio of standard faces size
Product is determined as the face size of the target camera acquisition face.
6. according to the method described in claim 4, it is characterized in that, determining the target camera according to the coloration test card
Clarity include:
All gridiron patterns in the coloration test card are positioned, determine each tessellated location information；
Each tessellated pixel value is determined according to each tessellated location information；
According to the mean value of all tessellated pixel values in coloration test card described in each tessellated calculated for pixel values or
Variance；
The pixel value mean value or variance of coloration test card according to the pre-stored data and the mapping relations of the clarity of camera determine
The clarity of the corresponding target camera of the mean value or variance of all tessellated pixel values in the coloration test card.
7. according to the method described in claim 4, it is characterized in that, determining the target camera according to the gradation test card
Brightness value include:
Gray scale lattice in the gradation test card are positioned, determine the location information of each gray scale lattice；
The weight and brightness of each gray scale lattice are obtained according to the location information of each gray scale lattice；
The sum of products of the weight of each gray scale lattice and brightness is determined as to the brightness value of the target camera.
8. according to the method described in claim 4, it is characterized in that, according to the brightness value and the color of the target camera
Degree test card determines that the color saturation of the target camera includes:
The chromatic value of the target camera is determined according to the coloration test card in the following manner:
Wherein, describedRespectively the first image is transformed under the color opposition space space LAB from rgb space
The corresponding chromatic value of color opposition dimension a, b,The color for being standard picture under the space LAB opposes dimension a, b
Corresponding chromatic value；
The color that the difference of the chromatic value of the target camera and the brightness value is determined as the target camera is satisfied
And degree.
9. method according to any one of claim 1 to 8, which is characterized in that including by the acquisition of target camera
Before first image of test card, the method also includes:
The target camera is obtained under different shooting conditions to the test card, one or more facial images, target pair
As shooting obtained multiple second images；
The Image quality measures of each second image in the multiple second image are obtained by the test card respectively, wherein
Described image qualitative character includes the clarity, the face size, the color saturation and the brightness value；
Recognition of face is carried out to the multiple second image respectively, obtains the first face characteristic of the target object, Yi Jisuo
State the second face characteristic of one or more facial images；
The first face characteristic of target object described in the multiple second image standard corresponding with the target is determined respectively
Second face characteristic of the first similarity of face characteristic and one or more of facial images with it is one or more of
Second similarity of the standard faces feature of facial image；
Calculate separately the average similarity of first similarity and second similarity in the multiple second image；
Image quality measures in described image quality standard are determined according to the average similarity in the multiple second image
Range.
10. according to the method described in claim 9, it is characterized in that, according to the average phase in the multiple second image
Include: like the range for determining Image quality measures in described image quality standard is spent
The corresponding Image quality measures of average similarity maximum in the multiple second image are determined as the first standard drawing image quality
Measure feature；
The corresponding Image quality measures of minimum average B configuration similarity in the multiple second image are determined as the second standard drawing image quality
Measure feature；
The range for determining Image quality measures in described image quality standard is more than or equal to second standard image quality
Feature, and it is less than or equal to the second standard image quality feature.
11. a kind of detection device of camera characterized by comprising
First obtains module, the first image shot for obtaining target camera to test card, wherein the test card
Including reflectance chart, coloration test card and gradation test card；
Identification module, the reflectance chart in the first image for identification, and identified by the reflectance chart
The coloration test card and the gradation test card；
First determining module, for being determined according to the reflectance chart, the coloration test card and the gradation test card
The objective image quality feature of the first image；
Second determining module, for determining institute according to the objective image quality feature and predetermined image quality criteria
State the image quality testing result of the first image.
12. device according to claim 11, which is characterized in that the identification module includes:
First identification submodule, for being positioned to the first image Plays test card, with the determination standard testing
The position of card, and identify the reflectance chart；
First determines submodule, for determining position and the institute of the coloration test card according to the position of the reflectance chart
State the position of gradation test card；
Second identification submodule, for identifying the coloration test card according to the position of the coloration test card, and according to institute
The position for stating gradation test card identifies the gradation test card.
13. device according to claim 12, which is characterized in that described first identifies that submodule includes:
Retrieval unit is retrieved for the image outline to the first image, to determine in the first image comprising the
The target area of one test card graphic；
Judging unit, for judging whether the first test card graphic is rectangle by multilevel logic；
Converting unit, in the case where the judgment result is yes, described first in the target area being tested card graphic
It is converted, the second test card graphic after being converted；
First positioning unit, for being positioned to reflectance chart described in the second test card graphic, described in determination
The position of reflectance chart.
14. a kind of computer-readable storage medium, the storage medium includes the program of storage, wherein described program operation
Method described in 1 to 10 any one of Shi Zhihang the claims.
15. a kind of electronic device, including memory and processor, which is characterized in that be stored with computer journey in the memory
Sequence, the processor are arranged to execute side described in any one of claims 1 to 10 by the computer program
Method.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910944618.6A CN110493595B (en) | 2019-09-30 | 2019-09-30 | Camera detection method and device, storage medium and electronic device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910944618.6A CN110493595B (en) | 2019-09-30 | 2019-09-30 | Camera detection method and device, storage medium and electronic device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110493595A true CN110493595A (en) | 2019-11-22 |
| CN110493595B CN110493595B (en) | 2022-12-06 |
Family
ID=68544827
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910944618.6A Active CN110493595B (en) | 2019-09-30 | 2019-09-30 | Camera detection method and device, storage medium and electronic device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110493595B (en) |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111861980A (en) * | 2020-05-29 | 2020-10-30 | 合肥联宝信息技术有限公司 | Imaging detection method, electronic equipment and computer readable storage medium |
| CN112492296A (en) * | 2020-11-12 | 2021-03-12 | 北京环境特性研究所 | Imaging quality evaluation system and imaging quality evaluation method |
| CN112927183A (en) * | 2021-01-13 | 2021-06-08 | 上海商米科技集团股份有限公司 | Lens module detection method and system of specific image recognition equipment |
| CN113705389A (en) * | 2021-08-13 | 2021-11-26 | 北京市商汤科技开发有限公司 | Face recognition module testing method and device, storage medium and electronic equipment |
| CN114125419A (en) * | 2021-11-26 | 2022-03-01 | 西安诺瓦星云科技股份有限公司 | Camera adjusting method and device in multi-camera system and multi-camera system |
| CN115049658A (en) * | 2022-08-15 | 2022-09-13 | 合肥的卢深视科技有限公司 | RGB-D camera quality detection method, electronic device and storage medium |
| CN116055712A (en) * | 2022-08-16 | 2023-05-02 | 荣耀终端有限公司 | Method, device, chip, electronic equipment and medium for determining film forming rate |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090059028A1 (en) * | 2006-10-02 | 2009-03-05 | Nikiforos Kollias | Imaging Standard Apparatus and Method |
| CN102466945A (en) * | 2010-11-19 | 2012-05-23 | 北京海鑫智圣技术有限公司 | LED supplementary lighting and image clipping evaluation system in standard image acquisition device |
| US20130057706A1 (en) * | 2011-09-04 | 2013-03-07 | Victor Steinberg | Video quality analyzer |
| CN103927520A (en) * | 2014-04-14 | 2014-07-16 | 中国华戎控股有限公司 | Method for detecting human face under backlighting environment |
| CN204733297U (en) * | 2015-07-15 | 2015-10-28 | 深圳市明宇通检测有限公司 | A kind of image quality test system |
| CN106596073A (en) * | 2016-12-28 | 2017-04-26 | 歌尔科技有限公司 | Method and system for detecting image quality of optical system, and testing target plate |
| CN107657608A (en) * | 2017-09-25 | 2018-02-02 | 北京小米移动软件有限公司 | Picture quality determines method, apparatus and electronic equipment |
| US20190114760A1 (en) * | 2017-10-18 | 2019-04-18 | Gorilla Technology Inc. | Method of Evaluating the Quality of Images |
| CN110175990A (en) * | 2019-05-17 | 2019-08-27 | 腾讯科技（深圳）有限公司 | Quality of human face image determination method, device and computer equipment |
| CN110717458A (en) * | 2019-10-11 | 2020-01-21 | 北京地平线机器人技术研发有限公司 | Face recognition method and recognition device |
| WO2020243969A1 (en) * | 2019-06-06 | 2020-12-10 | 深圳市汇顶科技股份有限公司 | Facial recognition apparatus and method, and electronic device |
-
2019
- 2019-09-30 CN CN201910944618.6A patent/CN110493595B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090059028A1 (en) * | 2006-10-02 | 2009-03-05 | Nikiforos Kollias | Imaging Standard Apparatus and Method |
| CN102466945A (en) * | 2010-11-19 | 2012-05-23 | 北京海鑫智圣技术有限公司 | LED supplementary lighting and image clipping evaluation system in standard image acquisition device |
| US20130057706A1 (en) * | 2011-09-04 | 2013-03-07 | Victor Steinberg | Video quality analyzer |
| CN103927520A (en) * | 2014-04-14 | 2014-07-16 | 中国华戎控股有限公司 | Method for detecting human face under backlighting environment |
| CN204733297U (en) * | 2015-07-15 | 2015-10-28 | 深圳市明宇通检测有限公司 | A kind of image quality test system |
| CN106596073A (en) * | 2016-12-28 | 2017-04-26 | 歌尔科技有限公司 | Method and system for detecting image quality of optical system, and testing target plate |
| CN107657608A (en) * | 2017-09-25 | 2018-02-02 | 北京小米移动软件有限公司 | Picture quality determines method, apparatus and electronic equipment |
| US20190114760A1 (en) * | 2017-10-18 | 2019-04-18 | Gorilla Technology Inc. | Method of Evaluating the Quality of Images |
| CN110175990A (en) * | 2019-05-17 | 2019-08-27 | 腾讯科技（深圳）有限公司 | Quality of human face image determination method, device and computer equipment |
| WO2020243969A1 (en) * | 2019-06-06 | 2020-12-10 | 深圳市汇顶科技股份有限公司 | Facial recognition apparatus and method, and electronic device |
| CN110717458A (en) * | 2019-10-11 | 2020-01-21 | 北京地平线机器人技术研发有限公司 | Face recognition method and recognition device |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111861980A (en) * | 2020-05-29 | 2020-10-30 | 合肥联宝信息技术有限公司 | Imaging detection method, electronic equipment and computer readable storage medium |
| CN111861980B (en) * | 2020-05-29 | 2022-02-01 | 合肥联宝信息技术有限公司 | Imaging detection method, electronic equipment and computer readable storage medium |
| CN112492296A (en) * | 2020-11-12 | 2021-03-12 | 北京环境特性研究所 | Imaging quality evaluation system and imaging quality evaluation method |
| CN112492296B (en) * | 2020-11-12 | 2022-05-10 | 北京环境特性研究所 | Imaging quality evaluation system and imaging quality evaluation method |
| CN112927183A (en) * | 2021-01-13 | 2021-06-08 | 上海商米科技集团股份有限公司 | Lens module detection method and system of specific image recognition equipment |
| CN113705389A (en) * | 2021-08-13 | 2021-11-26 | 北京市商汤科技开发有限公司 | Face recognition module testing method and device, storage medium and electronic equipment |
| CN114125419A (en) * | 2021-11-26 | 2022-03-01 | 西安诺瓦星云科技股份有限公司 | Camera adjusting method and device in multi-camera system and multi-camera system |
| CN115049658A (en) * | 2022-08-15 | 2022-09-13 | 合肥的卢深视科技有限公司 | RGB-D camera quality detection method, electronic device and storage medium |
| CN116055712A (en) * | 2022-08-16 | 2023-05-02 | 荣耀终端有限公司 | Method, device, chip, electronic equipment and medium for determining film forming rate |
| CN116055712B (en) * | 2022-08-16 | 2024-04-05 | 荣耀终端有限公司 | Method, device, chip, electronic equipment and medium for determining film forming rate |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110493595B (en) | 2022-12-06 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110493595A (en) | The detection method and device of camera, storage medium and electronic device | |
| CN106056064B (en) | A kind of face identification method and face identification device | |
| US8675960B2 (en) | Detecting skin tone in images | |
| JP5837508B2 (en) | Posture state estimation apparatus and posture state estimation method | |
| EP2154630A1 (en) | Image identification method and imaging apparatus | |
| CN107659769B (en) | A kind of image pickup method, first terminal and second terminal | |
| CN101983507A (en) | Automatic redeye detection | |
| WO2007136332A1 (en) | Method and apparatus for identifying properties of an object detected by a video surveillance camera | |
| US20100074547A1 (en) | Method for discriminating focus quality of image pickup device | |
| CN110490214A (en) | The recognition methods and system of image, storage medium and processor | |
| CN111935479A (en) | Target image determination method and device, computer equipment and storage medium | |
| CN105718931A (en) | System And Method For Determining Clutter In An Acquired Image | |
| WO2005043295A2 (en) | Systems and methods relating to afis recognition, extraction, and 3-d analysis strategies | |
| CN114066877A (en) | Image screening method and device, electronic equipment and storage medium | |
| JP2010211498A (en) | Image processing program and image processing system | |
| JP5862071B2 (en) | Image processing apparatus, imaging apparatus, and program | |
| JP5704909B2 (en) | Attention area detection method, attention area detection apparatus, and program | |
| CN110110110A (en) | One kind is to scheme to search drawing method, device, electronic equipment and storage medium | |
| JP7387261B2 (en) | Information processing device, information processing method and program | |
| WO2020008711A1 (en) | Learning device, learning system, and learning method | |
| CN108769543B (en) | Method and device for determining exposure time | |
| CN109919128A (en) | Acquisition methods, device and the electronic equipment of control instruction | |
| CN109816628A (en) | Face evaluation method and Related product | |
| KR20190142931A (en) | Code authentication method of counterfeit print image and its application system | |
| CN111091053A (en) | Data analysis method, device, equipment and readable medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |